我是cassandra的新手,我遇到了一个问题.我创建了一个keypace demodb和一个表用户.该表有3列:id(int和主键),firstname(varchar),name(varchar).这个请求给我带来了好结果:
SELECT * FROM demodb.users WHERE id = 3;
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但是这一个:
SELECT * FROM demodb.users WHERE firstname = 'francois';
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不起作用,我收到以下错误消息:
InvalidRequest: code=2200 [Invalid query] message="No secondary indexes on the restricted columns support the provided operators: "
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此请求也不起作用:
SELECT * FROM users WHERE firstname = 'francois' ORDER BY id DESC LIMIT 5;
InvalidRequest: code=2200 [Invalid query] message="ORDER BY with 2ndary indexes is not supported."
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提前致谢.
我是所有这些Web开发的新手(我只知道在本地做事).我使用reveal.js进行了演示,我希望能够在线看到它(例如我的手机上).我知道我应该主持它,但我真的不知道该怎么做.我尝试使用幻灯片(reveal.js的在线编辑器)来做,但我不能添加脚本和这种东西(我在演示文稿中使用高级图表).如果你能给我一些建议,程序会很好.
我在 Heroku 上部署了一个应用程序,但问题是当我的应用程序发送电子邮件时,它没有在 URL 中附加我的服务器的名称:
content = Content("text/html", verification_email.format(user["first_name"],
url_for("register.display_register_form",
token=token.decode("utf-8"), external=True)))
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但是我在电子邮件中收到的链接是:
http:///register_account/DnsJpXw_QIcPYeDHEg_fipB2kRiJBUj2RI6I9cI4Yl4w6K9ohbZRMVqBInuV0aOsBT4Zqt69X8MfhNfnys4s-DAQmgu1OPBwmSQnzAELvdcCyiZtkJGSY8_dQ799FOewtBDkvqR1D8XHmvVxgaVqbwSjdEBnvFsBBHMQCic%3D/verify?external=True
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我对这个 URL 有问题:
///当服务器名称为空时,服务器名称才不会出现在 URL 中我该怎么做才能获得正确的 URL https://my-server-name/register_account...?
编辑
我尝试在我的 config.py 文件中设置以下变量:
SERVER_NAME = " http://my-server-58140.herokuapp.com "
它在我的路径中生成了错误,例如我无法访问任何 URL,之前可以访问以下 URL,但在定义我的SERVER_NAME时不再访问它:
http://my-server-58140.herokuapp.com/home
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编辑
我的烧瓶应用程序已配置:
SERVER_NAME = os.environ.get('SERVER_NAME')
DEBUG = True
BASE_DIR = os.path.abspath(os.path.dirname(__file__))
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在0.0.0.0:5000我的本地主机和:my-server-58140.herokuapp.com在我的生产服务器上将环境变量设置为
我正在尝试执行一个合并 2 个 json 文件的 python 脚本,例如:
第一个文件:students.json
{"John Smith":{"age":16, "id": 1}, ...., "Paul abercom":{"age":18, "id": 764}}
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第二个文件:teacher.json
{"Agathe Magesti":{"age":36, "id": 765}, ...., "Tom Ranliver":{"age":54, "id": 801}}
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因此,为了不丢失任何信息,我第一次修改文件以添加每个人的状态,如下所示:
{"John Smith":{"age":16, "id": 1, "status":"student"}, ...., "Paul abercom":{"age":18, "id": 764, "status":"student"}}
{"Agathe Magesti":{"age":36, "id": 765, "status":"teacher"}, ...., "Tom Ranliver":{"age":54, "id": 801, "status":"teacher"}}
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为此,我执行了以下代码:
import pandas as pd
type_student = pd.read_json('student.json')
type_student.loc["status"] = "student"
type_student.to_json("testStudent.json")
type_teacher = pd.read_json('teacher.json')
type_teacher.loc["status"] = "teacher"
type_teacher.to_json("testTeacher.json")
with open("testStudent.json") as data_file:
data_student = json.load(data_file)
with open("testTeacher.json") as data_file: …Run Code Online (Sandbox Code Playgroud) 我有以下两个数据帧,第一行看起来像:
['station_id', 'country', 'temperature', 'time']
['12', 'usa', '22', '12:04:14']
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我想按照'法国'中前100个站点的降序显示平均温度.
在pyspark中实现它的最佳方法(效率最高)是什么?
我正在尝试构建一个 Flask API,我有一个端点应该创建用户,另一个端点应该检查数据库中是否存在用户:
@API.route('/users/', methods=['POST'])
def new_user():
user_json = json.loads(request.get_json())
first_name = user_json.get('first_name')
last_name = user_json.get('last_name')
email = user_json.get('email')
password = user_json.get('password')
# Call the other endpoint here
if response == 400:
try:
user = User(first_name=first_name, last_name=last_name, email=email, password=password)
db.session.add(user)
db.session.commit()
return jsonify(user=user.to_json()), 200
except:
return jsonify(error=500), 500
else:
return jsonify(user=user.to_json()), 409
@API.route('/users/<string:email>', methods=['GET'])
def is_present(email):
user = User.query.filter_by(email=email).first()
if user:
print(user)
return jsonify(user=user.to_json()), 200
else:
return jsonify(error=404), 404
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问题是我不知道is_present在new_user端点中调用我的最佳方法是什么。我应该使用吗requests.get?或者 Flask 中有其他特定的东西可以这样做吗?
我在Flask中开发了一个有效的应用程序.我尝试将我的环境从2.7版升级到3.6版.当我点击正在调用表单的端点时它生成了以下错误:
Traceback (most recent call last):
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/app.py", line 1997, in __call__
return self.wsgi_app(environ, start_response)
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/app.py", line 1985, in wsgi_app
response = self.handle_exception(e)
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/app.py", line 1540, in handle_exception
reraise(exc_type, exc_value, tb)
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/_compat.py", line 33, in reraise
raise value
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/app.py", line 1982, in wsgi_app
response = self.full_dispatch_request()
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/app.py", line 1614, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/app.py", line 1517, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/_compat.py", line 33, in reraise
raise value
File "/Users/Melvyn/Documents/personnel/python/TheSwitchWebApp/venv/lib/python3.6/site-packages/flask/app.py", line 1612, …Run Code Online (Sandbox Code Playgroud) 我在Elasticsearch中有一个具有以下ID的文档:AVosj8FEIaetdb3CXpP-我正在尝试访问tf-idf字段中的每个单词,我做了以下工作:
GET /cnn/cnn_article/AVosj8FEIaetdb3CXpP-/_termvectors
{
"fields" : ["author_wording"],
"term_statistics" : true,
"field_statistics" : true
}'
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我得到的答复是:
{
"_index": "dailystormer",
"_type": "dailystormer_article",
"_id": "AVosj8FEIaetdb3CXpP-",
"_version": 3,
"found": true,
"took": 1,
"term_vectors": {
"author_wording": {
"field_statistics": {
"sum_doc_freq": 3408583,
"doc_count": 16111,
"sum_ttf": 7851321
},
"terms": {
"318": {
"doc_freq": 4,
"ttf": 4,
"term_freq": 1,
"tokens": [
{
"position": 121,
"start_offset": 688,
"end_offset": 691
}
]
},
"742": {
"doc_freq": 1,
"ttf": 1,
"term_freq": 1,
"tokens": [
{
"position": 122,
"start_offset": 692, …Run Code Online (Sandbox Code Playgroud) 我应用 K-mean 算法使用 scikit learn 对一些文本文档进行分类并显示聚类结果。我想在相似度矩阵中显示我的集群的相似度。我在 scikit 学习库中没有看到任何允许这样做的工具。
# headlines type: <class 'numpy.ndarray'> tf-idf vectors
pca = PCA(n_components=2).fit(headlines)
data2D = pca.transform(to_headlines)
pl.scatter(data2D[:, 0], data2D[:, 1])
km = KMeans(n_clusters=4, init='k-means++', max_iter=300, n_init=3, random_state=0)
km.fit(headlines)
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有什么方法/库可以让我轻松绘制这个余弦相似度矩阵?
我是cassandra的新手,我尝试将一组数据添加到表中.我的表看起来像:
CREATE TABLE myTable (id int, name varchar, mySet set<uuid>, PRIMARY KEY (id));
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我遇到的问题是当我做我的请求时,类型不兼容,Java中的集合的字符串表示是[uuid1,uuid2,...],而cql中的表示是{'uuid1','uuid2', ...}
session.execute("INSERT INTO myTable (id , name, mySet) VALUES (" + myID + ", '" + myName +"' ," + mySet + ");");
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所以,如果有一个函数或库可以直接解决这个问题,你知道吗?非常感谢.
python ×6
flask ×3
python-3.x ×3
cassandra ×2
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apache-spark ×1
api ×1
cqlsh ×1
heroku ×1
hosting ×1
java ×1
json ×1
matplotlib ×1
nlp ×1
pandas ×1
pyspark ×1
python-2.7 ×1
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tf-idf ×1
versioning ×1
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